Welcome to issue 349 of NoSQL Weekly. Let's get straight to the links this week.
 

Articles, Tutorials and Talks

How to use Redis for real-time stream processing
An in-depth guide to overcoming fast data ingestion challenges with Redis Pub/Sub, Redis Lists, and Redis Sorted Sets.
 
Indexing MongoDB with ElasticSearch
A Simple Autocomplete Index Project.

Compiled GraphQL as a database query language
For nearly a year now, Kensho has been using GraphQL in a highly unusual way — by compiling GraphQL queries directly into a single, optimized graph database query. By hiding the complexity of the underlying database behind an expressive and easy-to-use GraphQL layer, we have been able to prototype and release new functionality to our clients in record time. Now, we are excited to release our GraphQL compiler as an open-source project!

Introducing S3Guard: S3 Consistency for Apache Hadoop
This article introduces a new Apache Hadoop feature called S3Guard. S3Guard addresses one of the major challenges with running Hadoop on Amazon’s Simple Storage Service (S3), eventual consistency. We outline the problem of S3’s eventual consistency, how it affects Hadoop workloads, and explain how S3Guard works.

Azure Functions with Couchbase Server
Azure Functions are Microsoft’s answer to Amazon’s Lambdas or Google’s Cloud Functions (aka “serverless” architecture). They give you a way to deploy small pieces of code, and let Azure handle the underlying server. There are more options in Azure Functions beyond simple HTTP events (e.g. Blob triggers, GitHub webhooks, Azure Storage queue triggers, etc). But, for this post, I’m going to focus on just HTTP events. I’ll create simple “Get” and “Set” endpoints that interact with Couchbase Server.

Efficient Graph Algorithms in Neo4j
You can use these graph algorithms on your connected data to gain new insights more easily within Neo4j. You can use these graph analytics to improve results from your graph data, for example by focusing on particular communities or favoring popular entities.

Provision CouchDB users with Auth0

Schema migrations with Cassandra

Neo4j Bolt Drivers Roundtable

Hadoop and Spark on Docker: Ten Things You Need to Know

A Game of Data and GraphQL


Interesting Projects, Tools and Libraries

TiSpark 
TiSpark is a thin layer built for running Apache Spark on top of TiDB/TiKV.

awesome-hbase
A curated list of awesome HBase projects and resources.

graphql-cli
Swiss Army Knife for your GraphQL Project.

GrapheneDB
Simple Ruby Wrapper for the GrapheneDB API.


New Releases

CouchDB 2.1
CouchDB 2.1 addresses most of the issues people found with the initial release of 2.0. And aside from a few new features, there has been a major focus on release tooling in a way that the project is now in a position to make more regular and more stable releases going forward. This means faster bug fixes and faster new features for all CouchDB users.


Upcoming Events and Webinars

Webinar: ReadConcern and WriteConcern
How do you make sure that your write operations are durable within a replica set? How do you make sure that your read operations do not see those writes that are not yet durable? This talk will cover the mechanics of ensuring durability of writes via write concern and how to prevent reading of stale data in MongoDB using read concern. We will discuss the decision flow for selecting an appropriate level of write concern, as well as associated tradeoffs and several practical use cases and examples.

Real-time Recommender Systems Made Easy with Neo4j - London, United Kingdom
Real-time recommender systems are one of the sweetspot use cases for native graph databases. Key goals for a good recommender system include relevance, novelty, serendipity and recommendation differentiation. In this talk, Pieter will demonstrate how you can have full and accurate control of the recommender system with Neo4j, interactive response at scale, and "on the fly" tuning for a fast time to market. 

BigData.be Meetup August 2017 - Brussels 
There will be following talks

  • Big data: A Catalog and how to build it
  • Data governance tools 


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